Risk factor analysis and establishment of a predictive model for complications of elderly advanced gastric cancer with Clavien-Dindo classification ≥ II grade.

Background: The occurrence of complications following radical gastrectomy for gastric cancer significantly impacts patients' quality of life. Elderly patients are susceptible to postoperative complications. This study seeks to investigate the risk factors associated with Clavien-Dindo ≥IIgrade complications following radical gastrectomy for advanced gastric cancer in elderly patients, develop a nomogram risk prediction model, and validate its accuracy.

Prediction of the risk of severe small bowel obstruction and effects of Houpu Paiqi mixture in patients undergoing surgery for small bowel obstruction.

Aim: Small bowel obstruction is a common condition that requires emergency surgery. Slow recovery of bowel function after surgery or the occurrence of one or more complications can exacerbate the disease and result in severe small bowel obstruction (SSBO), significantly impacting recovery. It is characterized by a failure to regain enteral nutrition promptly, requiring long-term intensive care.

Machine learning was used to predict risk factors for distant metastasis of pancreatic cancer and prognosis analysis.

Background: The mechanisms of distant metastasis in pancreatic cancer (PC) have not been elucidated, and this study aimed to explore the risk factors affecting the metastasis and prognosis of metastatic patients and to develop a predictive model.

Method: Clinical data from patients meeting criteria from 1990 to 2019 were obtained from the Surveillance, Epidemiology, and End Results (SEER) database, and two machine learning methods, random forest and support vector machine, combined with logistic regression, were used to explore risk factors influencing distant metastasis and to create nomograms. The performance of the model was validated using calibration curves and ROC curves based on the Shaanxi Provincial People's Hospital cohort.